Improved max-log map turbo decoding using maximum mutual information combining

The demand for low-cost and low-power decoder chips has resulted in renewed interest in low-complexity decoding algorithms. In this paper a novel modification of the Max-Log-MAP algorithm is proposed for use in a turbo decoding process. This is achieved by scaling the a priori information by correction weights at each iteration, in order to maximize the exchange of mutual information between the component decoders. It is shown that the proposed technique results in a performance which approaches that of a turbo decoder using the optimum MAP algorithm, while maintaining the advantages of low complexity and insensitivity to input scaling inherent in the Max-Log-MAP algorithm. A second contribution of this paper is a method for off-line computation of the optimum weight values. The convergence behaviour of the proposed decoder is analysed via extrinsic information transfer (EXIT) charts.